import sys
import numpy as np
import pandas as pd
import seaborn as sns
sns.set_theme()

results_folder = 'mmvec_major_taxa_1'
results_base_name = 'latent_dim_3_input_prior_1.00_output_prior_1.00_beta1_0.90_beta2_0.95'

table = pd.read_table(results_folder + '/' + results_base_name + '_ranks.txt', index_col=0)
table.head()

	Propionibacteriaceae	Staphylococcus caprae or capitis	Staphylococcus epidermidis	Staphylococcus hominis	Other Staphylococci	Polyomavirus HPyV6	Polyomavirus HPyV7	Merkel Cell Polyomavirus	Malasseziaceae	Corynebacteriaceae	Micrococcaceae	Other families
featureid
X940001	0.135536	0.061269	0.043672	0.044610	0.184495	0.037716	-0.020562	0.100228	0.186801	0.315386	0.153056	0.079198
X940002	-0.007746	-0.194599	-0.286544	-0.040674	-0.171444	-0.101813	-0.153303	-0.118492	-0.160680	-0.099536	-0.164102	-0.228855
X940005	-0.069363	-0.284181	-0.334273	-0.414055	-0.135930	0.357771	-0.014280	-0.047856	-0.396604	-0.174711	-0.159746	-0.241668
X940007	0.365357	0.282299	0.251389	0.551716	0.228546	0.003074	0.195018	0.249597	0.381006	0.334098	0.264940	0.242767
X940010	0.335508	0.006827	0.755825	0.447261	0.298167	0.484671	0.768211	0.686417	-0.164282	0.371776	0.572235	0.496835

#table['Selected'] = np.logical_and(np.logical_and(table['Propionibacteriaceae']<0.4, table['Staphylococcus epidermidis']>0.9), table['Propionibacteriaceae'] - table['Staphylococcus epidermidis']<-1)
table['Selected'] = np.isin(table.index,
                            ['X940203', 'X940589', 'X940625', 'X940925', 'X940936', 'X942191',
                             'X942237', 'X950023', 'X950028', 'X950056', 'X950157', 'X950173',
                             'X950193', 'X950225', 'X950228', 'X950233', 'X950254', 'X950396',
                             'X950485', 'X950584', 'X950661', 'X950999', 'X960035', 'X960242',
                             'X960306', 'X960421', 'X960463', 'X960465', 'X960712', 'X960726',
                             'X960934', 'X961553', 'X961686', 'X970018', 'X970091', 'X970092',
                             'X970232', 'X970283', 'X970327', 'X970342', 'X970633', 'X970680']
                           )
table.sort_values('Selected', inplace=True)
sns.relplot(
    table,
    y='Propionibacteriaceae', x='Staphylococcus epidermidis', hue='Selected'
)

<seaborn.axisgrid.FacetGrid at 0x7f2c34ef8790>

sns.pairplot(table, hue='Selected')

<seaborn.axisgrid.PairGrid at 0x7f2c34cf0590>

for i in table.columns[:-1]:
    sns.displot(table, x=i, hue='Selected', multiple='stack')